As conventional change region detecting methods, following methods may be named.
The first method is a background differential method in which a change region is detected based on the brightness difference between a learned average background image and an inputted image (Kentaro Toyama, John Krumm, Barry Brumitt, and Brian Meyers. Wallflower: Principles and practice of background maintenance. Proceedings of the 7th IEEE International Conference on Computer Vision (ICCV 1999), PP. 255-261, September 1999. 1).
The second method is a texture differential method in which a change region is detected based on difference between a learned background texture and an inputted image texture (Yutaka Sato, Shunichi Kaneko and Satoru Igarashi. Robust Object Detection and Separation Based on Peripheral Increment Sign Correlation Image. Institute of Electronics, Information and Communication Engineers Transactions, Vol. J84-D-II, No. 12, PP. 2585-2594, 2001. Hereinafter, referred to as “SATO”).
The third method is a method which, based on the magnitude of an edge amount of a learned background, determines a change region based on the lowness of normalized correlation and an edge decrease quantity with respect to a region of large edge quantity, and determines the change region based on the edge increase quantity with respect to a region of small edge quantity (JP-A-2003-162724).
However, the background differential method which constitutes the first method has a drawback that the whole brightness change attributed to the illumination change is erroneously detected as the change attributed to a figure or the like.
The texture differential method which constitutes the second method may sufficiently cope with the change of brightness and may perform a small number of erroneous detections but has a drawback that the accurate detection cannot be performed when neither a background nor a figure or the like has texture.
The third method determines the change range based on the increase or decrease of the edge and hence, the method has a drawback that the accurate detection cannot be performed when neither a background nor an invading object or the like has texture.
Accordingly, it is an object of the present invention to provide a change region detection device and a change region detecting method which can prevent the omission of detection while suppressing errors in detecting a change region.